Online prediction of the running time of tasks
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
On the stability of a partially accessible multi-station queue with state-dependent routing
Queueing Systems: Theory and Applications
Computer Systems Performance Evaluation and Prediction
Computer Systems Performance Evaluation and Prediction
Nonfunctional Requirements: From Elicitation to Conceptual Models
IEEE Transactions on Software Engineering
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
Model-Based Performance Prediction in Software Development: A Survey
IEEE Transactions on Software Engineering
An approach for quality of service adaptation in service-oriented Grids: Research Articles
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
QoS-Aware Model Driven Architecture through the UML and CIM
EDOC '06 Proceedings of the 10th IEEE International Enterprise Distributed Object Computing Conference
Runtime prediction of queued behaviour
QoSA'06 Proceedings of the Second international conference on Quality of Software Architectures
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Self-adaptive systems are capable of changing their behaviour at runtime to meet target constraints. An important research question is how quality of service models can inform runtime adaptation. This paper presents a solution to the problem by application of control theory to improve performance of queued systems by means of architectural adaptation. In a paper presented at the previous year's QoSA conference, we showed how Auto-Regressive Integrated Moving Average techniques can be utilized to forecast how Quality of Service (QoS) characteristics are likely to evolve in the near future. This is particularly important in cases where systems can be adapted to counter QoS constraint violations. In this paper, we show how, given a similar type of QoS characteristic forecasts, strategies of architectural adaptation can be implemented that pre-emptively avoid QoS violations. The novelty of our approach is that we use classical control theory to ensure that our adaptation strategies are stable, in the sense that they do not oscillate between choices. We provide a description of how our control theoretic model can be implemented using context-based interception in .NET via model driven engineering.